Loss Of Genetic Gain Research Articles

Optimization Strategies to Adapt Sheep Breeding Programs to Pasture-Based Production Environments: A Simulation Study.

Strong differences between the selection (indoor fattening) and production environment (pasture fattening) are expected to reduce genetic gain due to possible genotype-by-environment interactions (G × E). To investigate how to adapt a sheep breeding program to a pasture-based production environment, different scenarios were simulated for the German Merino sheep population using the R package Modular Breeding Program Simulator (MoBPS). All relevant selection steps and a multivariate pedigree-based BLUP breeding value estimation were included. The reference scenario included progeny testing at stations to evaluate the fattening performance and carcass traits. It was compared to alternative scenarios varying in the progeny testing scheme for fattening traits (station and/or field). The total merit index (TMI) set pasture-based lamb fattening as a breeding goal, i.e., field fattening traits were weighted. Regarding the TMI, the scenario with progeny testing both in the field and on station led to a significant increase in genetic gain compared with the reference scenario. Regarding fattening traits, genetic gain was significantly increased in the alternative scenarios in which field progeny testing was performed. In the presence of G × E, the study showed that the selection environment should match the production environment (pasture) to avoid losses in genetic gain. As most breeding goals also contain traits not recordable in field testing, the combination of both field and station testing is required to maximize genetic gain.

Benefits of genomic evaluation in aquaculture breeding programs with separate rearing of families

A common type of rearing in aquaculture selective breeding programs is to keep families in separate tanks until fish is large enough to be individually tagged. This type of rearing introduces an environmental effect common to the members of the same family which can be difficult to be disentangled from genetic effects when traditional BLUP evaluation is used. The use of genomic evaluation could lead to a better prediction of these effects as markers can capture more accurately genetic relationships between fish raised in different tanks and between full-sibs raised in the same tank. The objective of this simulation study was to predict the benefit of genomic evaluation (GBLUP) when compared to BLUP in the presence of common environmental effects. Models that included or excluded these effects when they were present were compared. Populations with two different levels of linkage disequilibrium were generated. The heritability of the selected trait was 0.4 and three different proportions of phenotypic variance due to common environmental effect (0.0, 0.1 and 0.3) were considered. Nested mating designs where each male was mated to two females were simulated to create 200 full-sib families with 10 or 50 fish per family. GBLUP was less affected than BLUP by the presence of common environmental effects. The loss in genetic gain ranged from 0% to 4% with GBLUP and from 2% to 7% with BLUP. As a consequence, the benefit of GBLUP increased in the presence of common environmental effects, and the extra benefit increased with increasing linkage disequilibrium and family size. In the absence of these effects, genetic gain from GBLUP was up 20% higher than from BLUP and in their presence, genetic gain from GBLUP was 27% higher than from BLUP. Although GBLUP always led to lower inbreeding than BLUP, there were no extra benefits in terms of extra reductions in the presence of common environmental effects. Finally, when these effects were present but ignored in the evaluation model, the loss in genetic gain was moderate but inbreeding increased dramatically, particularly in BLUP scenarios.

Genetic diversity and population structure of Boer and Nubian goats in Mexico

In Mexico, since 2010 the Asociación Mexicana de Criadores de Ganado Caprino de Registro has been undertaking annual national genetic evaluations for the Boer and Nubian goat breeds. Mexican pedigree goat farmers are concerned with maintaining a reasonable high genetic diversity and a low level of inbreeding without loss of genetic gain. This study aimed to assess the genetic diversity and to describe the population structure of the Boer and Nubian goat breeds in Mexico using pedigree analyses to support the development of strategies for breeding programs. Herdbook information collected between 1994–2017 for Boer and from 1991 to 2017 for Nubian were utilized. The information included pedigree records on 18,947 animals for Boer (141 flocks) and 13,744 animals for Nubian (99 flocks). The effective number of founders ( f e ) were 504 and 203, and the effective number of ancestors ( f a ) were 253 and 88, for Boer and Nubian, respectively. The ratio f a / f e was 0.50 for Boer and 0.43 for Nubian, indicating the existence of population bottlenecks. The average inbreeding and relatedness coefficients were 1.02 and 0.28 % for Boer and, 1.39 and 1.04 % for Nubian. The number of most influential ancestors that explained 50 % of the genetic diversity in the population were 109 for Boer and 38 for Nubian. The average generation interval estimated through the four gametic paths was 3.27 ± 0.03 yr for Boer and 4.63 ± 0.06 yr for Nubian. Realized effective population size, computed from the individual increase in inbreeding, was 61.3 ± 24.5 for Boer and 69.3 ± 22.8 for Nubian (kids born from 2013 to 2017 were considered as the reference population for both breeds). The average equivalent completed generations, as a measure of pedigree completeness, were 2.02 for Boer and 2.88 for Nubian. The pedigree completeness index increased over time for both breeds. The results revealed the loss of genetic diversity and the presence of genetic bottlenecks for both populations. The study of the genetic diversity on these populations must continue to prevent the decrease in genetic progress and genetic variability. Additionally, a mating policy that simultaneously allows low levels of inbreeding, high levels of genetic diversity and maximum genetic progress, must be designed.

Genomic selection improves the possibility of applying multiple breeding programs in different environments

One joint breeding program (BP) for different dairy cattle environments can be advantageous for genetic gain depending on the genetic correlation between environments (rg). The break-even correlation (rb) refers to the specific rg where genetic gain with 1 joint BP is equal to the genetic gain of 2 environment-specific BP. One joint BP has the highest genetic gain if rg is higher than rb, whereas 2 environment-specific BP have higher genetic gain if rg is lower than rb. Genetic gain in this context is evaluated from a breeding company's perspective that aims to improve genetic gain in both environments. With the implementation of genomic selection, 2 types of collaboration can be identified: exchanging breeding animals and exchanging genomic information. The aim of this study was to study genetic gain in multiple environments with different breeding strategies with genomic selection. The specific aims were (1) to find rb when applying genomic selection; (2) to assess how much genetic gain is lost when applying a suboptimal breeding strategy; (3) to study the effect of the reliability of direct genomic values, number of genotyped animals, and environments of different size on rb and genetic gain; and (4) to find rb from each environment's point of view. Three breeding strategies were simulated: 1 joint BP for both environments, 2 environment-specific BP with selection of bulls across environments, and 2 environment-specific BP with selection of bulls within environments. The rb was 0.65 and not different from rb with progeny-testing breeding programs when compared at the same selection intensity. The maximum loss in genetic gain in a suboptimal breeding strategy was 24%. A higher direct genomic value reliability and an increased number of genotyped selection candidates increased genetic gain, and the effect on rb was not large. A different size in 2 environments decreased rb by, at most, 0.10 points. From a large environment's point of view, 1 joint BP was the optimal breeding strategy in most scenarios. From a small environment's point of view, 1 joint BP was only the optimal breeding strategy at high rg. When the exchange of breeding animals between environments was restricted, genetic gain could still increase in each environment. This was due to the exchange of genomic information between environments, even when rg between environments were as low as 0.4. Thus, genomic selection improves the possibility of applying environment-specific BP.

Optimization of Nile tilapia breeding schemes for monosex culture conditions in smallholder production systems

The aim of this study was to optimize the design of a nucleus Nile tilapia breeding program for harvest weight, growth rate and survival in the presence of genotype by environment interaction with monosex (MS) culture of all-male fish. A nucleus breeding program was deterministically simulated using pseudo-BLUP selection index theory, implemented in SelAction. First, we investigated the rates of genetic gain for growth rate, expressed as TGCms using different selection indexes with varying degrees of genotype by environment interaction (G×E), expressed as the genetic correlation (rg) between the nucleus and a monosex production environment. Selection strategies were (1) mass selection in nucleus only, (2) Best Linear Unbiased Prediction (BLUP) with full/half sib information from the nucleus fish only, and (3) BLUP with information from full and half sibs in the nucleus and in the monosex production environment. In the second step, we extended the breeding goal to include harvest weight (HWms) and survival (Sms) to derive desired weights and genetic gains for these breeding goal traits. Finally, we maximized genetic gains in Sms while restricting the loss in TGC to 5%. Results: the presence of G×E lowered accuracy of selection (rIH) which led to a loss in genetic gain for TGCms. At rg of 0.7 and less, incorporating half sib information from monosex sibs into the selection index resulted in higher genetic gains of TGCms. Using 8 offspring in the nucleus as selection candidates and 32 offspring in monosex production environment, resulted in highest accuracy with lowest rates of inbreeding. This index had the highest relative genetic gains in all rg tested, implying that this index is least sensitive to G×E. Phenotypic variance ratio had no effects on rIH but had effects on predicted genetic response. Maximizing gains for HWms and Sms caused a large reduction of genetic gain in TGCms. However, allowing a 5% loss of genetic gain in both TGCms and HWms resulted in a 33% increase in genetic improvement of Sms. A breeding goal that maximizes survival while restricting loss in TGC to 5% had the highest response in US$. Statement of relevanceThis is the first study that presents optimization of Nile tilapia breeding schemes for monosex culture conditions in smallholder production systems of the tropics.

Genotype by environment (climate) interaction improves genomic prediction for production traits in US Holstein cattle

Genotype by environment interaction (G × E) in dairy cattle productive traits has been shown to exist, but current genetic evaluation methods do not take this component into account. As several environmental descriptors (e.g., climate, farming system) are known to vary within the United States, not accounting for the G × E could lead to reranking of bulls and loss in genetic gain. Using test-day records on milk yield, somatic cell score, fat, and protein percentage from all over the United States, we computed within herd-year-season daughter yield deviations for 1,087 Holstein bulls and regressed them on genetic and environmental information to estimate variance components and to assess prediction accuracy. Genomic information was obtained from a 50k SNP marker panel. Environmental effect inputs included herd (160 levels), geographical region (7 levels), geographical location (2 variables), climate information (7 variables), and management conditions of the herds (16 total variables divided in 4 subgroups). For each set of environmental descriptors, environmental, genomic, and G × E components were sequentially fitted. Variance components estimates confirmed the presence of G × E on milk yield, with its effect being larger than main genetic effect and the environmental effect for some models. Conversely, G × E was moderate for somatic cell score and small for milk composition. Genotype by environment interaction, when included, partially eroded the genomic effect (as compared with the models where G × E was not included), suggesting that the genomic variance could at least in part be attributed to G × E not appropriately accounted for. Model predictive ability was assessed using 3 cross-validation schemes (new bulls, incomplete progeny test, and new environmental conditions), and performance was compared with a reference model including only the main genomic effect. In each scenario, at least 1 of the models including G × E was able to perform better than the reference model, although it was not possible to find the overall best-performing model that included the same set of environmental descriptors. In general, the methodology used is promising in accounting for G × E in genomic predictions, but challenges exist in identifying a unique set of covariates capable of describing the entire variety of environments.

Measuring the Inefficiency of Allowing Self‐Pollinated Alfalfa Progeny into Breeding Nurseries

Although alfalfa (Medicago sativa L.) is considered an outcrossing species, the self‐pollination incidence during insect pollination can be substantial, with an observed 30% average selfing rate. Despite this, alfalfa breeders utilizing space‐plant evaluation nurseries make no attempt to discriminate self‐pollination‐derived progeny (selfs) from outcross progeny. Due to alfalfa's substantial inbreeding depression, the selfed individuals have much lower breeder utility. This study examines an alfalfa space‐plant breeding nursery in which selfed and outcross progeny had been identified using DNA markers for the following phenotypic traits: plant vigor, fall height, fall dormancy, first and second winter survival, plant lodging, and profusion of flowering. Trait means, phenotypic and additive variances, and narrow‐sense heritabilities on a halfsib mean basis were determined for selfed and outcross progeny. For most traits, inbreeding depression was severe, with approximately 80% reductions in performance. Selfed progeny for most traits had reduced phenotypic variances compared with outcross progeny. No differences in estimated additive variance and heritabilities were observed between the two types of progeny. Assuming a 30% selfing rate and a selection intensity less than or equal to 10%, we would expect to select few if any selfed progeny from a space‐plant nursery that had plant vigor phenotypic distributions observed in this study. The estimated maximum loss in genetic gain due to the presence of selfed progeny in breeding nurseries for selection intensities from 1 to 10% was estimated at a 10% genetic gain reduction. We conclude that selfed progeny in breeding nurseries are a hindrance, and if possible, they should be minimized or eliminated.

Evaluation of breeding strategies for polledness in dairy cattle using a newly developed simulation framework for quantitative and Mendelian traits.

BackgroundIntensified selection of polled individuals has recently gained importance in predominantly horned dairy cattle breeds as an alternative to routine dehorning. The status quo of the current polled breeding pool of genetically-closely related artificial insemination sires with lower breeding values for performance traits raises questions regarding the effects of intensified selection based on this founder pool.MethodsWe developed a stochastic simulation framework that combines the stochastic simulation software QMSim and a self-designed R program named QUALsim that acts as an external extension. Two traits were simulated in a dairy cattle population for 25 generations: one quantitative (QMSim) and one qualitative trait with Mendelian inheritance (i.e. polledness, QUALsim). The assignment scheme for qualitative trait genotypes initiated realistic initial breeding situations regarding allele frequencies, true breeding values for the quantitative trait and genetic relatedness. Intensified selection for polled cattle was achieved using an approach that weights estimated breeding values in the animal best linear unbiased prediction model for the quantitative trait depending on genotypes or phenotypes for the polled trait with a user-defined weighting factor.ResultsSelection response for the polled trait was highest in the selection scheme based on genotypes. Selection based on phenotypes led to significantly lower allele frequencies for polled. The male selection path played a significantly greater role for a fast dissemination of polled alleles compared to female selection strategies. Fixation of the polled allele implies selection based on polled genotypes among males. In comparison to a base breeding scenario that does not take polledness into account, intensive selection for polled substantially reduced genetic gain for this quantitative trait after 25 generations. Reducing selection intensity for polled males while maintaining strong selection intensity among females, simultaneously decreased losses in genetic gain and achieved a final allele frequency of 0.93 for polled.ConclusionsA fast transition to a completely polled population through intensified selection for polled was in contradiction to the preservation of high genetic gain for the quantitative trait. Selection on male polled genotypes with moderate weighting, and selection on female polled phenotypes with high weighting, could be a suitable compromise regarding all important breeding aspects.Electronic supplementary materialThe online version of this article (doi:10.1186/s12711-016-0228-7) contains supplementary material, which is available to authorized users.

Improving initial trials in tree breeding using kinship and breeding values estimated in the wild: the case of Prosopis alba in Argentina

Most Argentinean forests have been lost by over exploitation and expansion of agricultural areas. The National breeding program for the native species Prosopis alba is still in its initial phase with only a few progeny trials installed from material collected in the wild and the first genetic studies are underway. Breeding value (BV) estimates based on pedigree data from a progeny trial were first compared to those derived by using microsatellite based kinship estimates to confirm the potential accuracy of g-best linear unbiased predictions (G-BLUP) when pedigree information is lacking. Afterwards, the possible genetic effects of alternative selection strategies to collect improved seeds from a wild population were evaluated. To achieve this goal the relationship among average genetic gain (predicted by G-BLUP), inbreeding and sampling size of the collected materials were weighed in a wild population consisting of trees of similar ages. The results obtained suggest that kinship estimates based on molecular data and breeding value predictions BV used for the selection of elite trees in wild populations may contribute to improve the genetic properties of the founder population. Controlling kinship allows reducing sampling size from 20 to 10 individuals per origin with no significant increase of inbreeding or loss of genetic gain. For a selected group of only ten top individuals per origin, the replacement of two strongly reduces the average group coancestry with minimal gain loss. Simultaneous selection for two traits by selection index might produce a gain of near 6 % in height and 2 % in diameter. The use of molecular marker information may contribute to reduce the time needed in a P. alba improvement program.

Genomic selection strategies to optimize the use of multiple ovulation and embryo transfer schemes in dairy cattle breeding programs

The aim of this study was to assess the impact of varying features of an open multiple ovulation and embryo transfer (MOET) nucleus used in a genomic dairy cattle breeding scheme on both genetic gain and inbreeding rates. The Viking Red breeding scheme served as a case study to design scenarios that were stochastically simulated. We analyzed the number of AI sires used in the breeding population, the number of flushed heifers, the number of flushings per heifer and the genotyping capacity allocated to young females. The results supported that setting up a MOET program in a genomic dairy cattle scheme increases genetic gain without increasing inbreeding rates when the MOET nucleus size and the number of AI sires in service are large enough. Secondly, it was shown that increasing the number of genotyped heifers could not compensate the loss in genetic gain caused by closing the MOET nucleus. On the contrary, when extending the flushing capacity of the MOET program, increasing the number of flushings per heifer had a greater impact on genetic gain, but also on inbreeding rates, than increasing the number of flushed females. So, when a constraint applies on the flushing capacity in an open MOET scheme and the achieved inbreeding rate permits it, it seems more relevant to increase the number of flushings per heifer than the number of flushed heifers. Results also indicated that the number of genotypings allocated to females had to be sufficient to get maximal returns from the MOET scheme. In this case study, little extra genetic gain could be obtained by extending the MOET scheme size with the initial genotyping strategy (800 genotyped females). Indeed, the genotyping capacity should permit to genotype all heifers produced in the MOET scheme to discriminate the best heifers within families, and should be also sufficient to identify the best heifers outside the MOET nucleus.

Genotype by environment interaction in the southern Swedish breeding population of Picea abies using new climatic indices

Genotype–environment interaction (G × E) has a critical impact on the design of a breeding programme and the resulting genetic gains. The aim of this study was to assess the incidence and predictability of G × E with respect to growth traits in the breeding population of Picea abies (L.) Karst. in southern Sweden. We used across-site genetic correlations as a measure of G × E and multiple linear regression to detect patterns in the correlations. As independent variables in the regression analysis, we used site and geographic factors as well as a comprehensive set of new climatic variables. A main result was that G × E was low to moderate with respect to the growth traits considered and largely unpredictable based on any of the geographic or climatic variables analyzed. However, it seems that the effects of late spring frost damage are important as they created significant differences in across-site correlations and we suggest that models describing frost risks should be developed. One major implication from this study is that the same genetic material could be used over larger areas in southern Sweden than recommended today with only a marginal or no loss in genetic gain.

Comparison of bivariate and multivariate joint analyses on the selection loss of beef cattle.

For genetic evaluation of beef cattle, univariate or bivariate analyses are often performed as an alternative to decrease the complexity of matrices and mathematical models compared to multivariate analysis, which considers a larger number of joint traits. The use of bivariate methods to calculate genetic predictors may cause bias in the estimation of breeding values and, as a consequence, reclassification of the rank of top-selected sires, resulting in a loss of genetic gain in future generations. The objective of this study was to compare the bivariate and multivariate joint methods of genetic evaluation, verifying the selection loss, and reclassification of the ranking of the best animals with different selection intensities. Records of 431,224 Nellore breed animals were evaluated for birth weight, weaning weight, post-weaning gain, muscle score, scrotal circumference, and selection index. The pedigree file consisted of 505,848 animals, including 218,727 males and 287,121 females. The predicted breeding values were obtained using the program PEST 2, and the complete pedigree analysis was performed by the PopReport software. The results showed that, for the four different selection intensities considered (TOP 10 and 1, 10, and 30%), selection loss and reclassification of animals in ranking, were detected for all traits evaluated when the two methods of analysis were compared.

Resposta à seleção de características de desempenho e morfométricas de tilápia-do-nilo ao longo do período de cultivo

Estudou-se a resposta à seleção para características de desempenho e morfométricas de tilápia-do-nilo (Oreochromis niloticus) em diferentes períodos de cultivo. Realizaram-se análises unicaracter para todas as características estudadas e as análises bicaracter, associando-se o ganho de peso diário, mensurado em quatro biometrias, com as características morfométricas obtidas ao final do período de cultivo. As herdabilidades estimadas para peso vivo, altura e comprimento de cabeça foram mais altas em análises unicaracter do que as estimadas em análises bicaracter. Os valores de correlações genéticas, fenotípicas, Pearson e Spearman foram positivas e crescentes com o avanço da idade dos animais. As respostas à seleção indireta foram 87% mais altas que as obtidas pela resposta direta, indicando que a seleção pode ser realizada precocemente, utilizando como critério de seleção o ganho de peso diário total medido em biometrias intermediárias, sem apresentar perdas expressivas no ganho genético.

Implementation of Optimum Contributions Selection in endangered local breeds: the case of the Menorca Horse population

Limiting the inbreeding rate (∆F) while maximizing genetic gain for any trait of economic interest is especially important in small populations of local breeds, like the Menorca Horse. In this breed, dressage performance is important for the profitability of the breed and should be accounted in the selection criterion. The aim of this study was to assess if a breeding programme aiming at improved dressage performance is feasible in such a small breed. To perform the analysis, animals that were currently available for breeding (between 3 and 20years) were used. Selection was based on the estimated breeding values for dressage obtained by BLUP. The pedigree and molecular coancestry between potential breeding horses was used (separately or in combination) to account for the restriction on ∆F. Results show that it is possible to avoid large increases in inbreeding while obtaining acceptable levels of genetic gain (i.e. a ∆F of 1% would imply a maximum loss in genetic gain of 2%). Thus, the Menorca Horse population is suitable for a management procedure which jointly optimizes the response to selection and the levels of variability and inbreeding (Optimal Contribution selection). Regarding the source of information used to calculate the relationships, molecular information would provide a greater range of solutions to increase genetic gain than using pedigree coancestry (gain was 1-4% higher for the same levels of restriction on the increase in inbreeding).

The effect of fertilization on genetic parameters in Picea abies clones in central Sweden and consequences for breeding and deployment

The aim of this study was to analyze the effect of repeated fertilizer application on the genetic parameters of Norway spruce. Genetic and environmental variances of growth and phenological traits were estimated to find differences between fertilized and control treatments in broad sense heritability and accuracy of estimated genotypic value. Furthermore, genotype×environment interactions (GxE) between the two treatments were investigated. Two Norway spruce clonal field trials in central Sweden were subjected to both treatments and were measured at various points in time up to a field age of 15years, to monitor the effects of fertilization. For growth traits, trees in the fertilized treatment exhibited lower environmental variance than those in the non-fertilized treatment; consequently, fertilization yielded higher heritability and greater accuracy of estimated genotypic value. Furthermore, the GxE increased as the effects of fertilization became more pronounced; the genetic correlation between treatments dropped to around 0.5 in the last measured growth period. For phenological traits, no GxE but a slight increase in heritability of prolepsis on the leader shoot was found. The results from this study show that, for the conditions encountered in central Sweden, Norway spruce clones should be tested and selected under the conditions in which they are to be deployed. If repeated fertilizer application is to be adopted under operational conditions, substantial losses in genetic gain for growth can be expected when using current selected clones due to the induced GxE. While the fertilized treatment yielded a higher heritability and accuracy of estimated genotypic value for growth traits than did the control, the Swedish Norway spruce breeding program will not benefit from fertilizing genetic field trials because the increased accuracy of estimated genotypic value is nullified by the GxE.

Consequences of elimination of the Rendement Napole allele from Danish Hampshire

An elimination programme was carried out to remove the dominant Rendement Napole mutation (RN(-) ) from Danish Hampshire pigs. We reasoned that during and after the elimination of the RN(-) allele, genetic gain of production traits decreased while rate of inbreeding in the population increased compared to the period prior to elimination. The hypothesis was tested by estimating the genetic gain in seven production traits and measuring the rate of inbreeding in the population prior to and during the elimination period. Genetic gain was reduced for quantitative traits daily gain(30-100 kg) and feed conversion ratio, while gain for ultimate-pH, lean meat percentage and slaughter loss were increased slightly. There were no changes in genetic gain for daily gain(birth-30 kg) and conformation. RN polymorphism affected several of the quantitative traits. The RN(-) mutation had a dominant effect on the traits daily gain(birth-30 kg) , daily gain(30-100 kg) , slaughter loss, lean meat percentage and ultimate-pH. It exhibited overdominance for feed conversion ratio and additive effect for conformation. Rate of inbreeding decreased during the elimination of RN(-) . Our findings indicate that the consequences of the elimination programme were not as serious as were feared and that a carefully designed preselection strategy may avoid unacceptable loss of genetic gain and excessive loss of genetic variation.

Prospects of performing multiple-country comparison of dairy sires for countries not participating in Interbull international genetic evaluations

International trade with genetic material has lead to the foundation of Interbull, an international organization that performs international evaluations of dairy bulls, enabling countries to obtain breeding values of foreign bulls on their on scale. Not all countries have the possibility to participate in the evaluations with their own national breeding values. The aim of this study was to find an alternative method that does not require national breeding values. Argentina was used as a representative of countries without national breeding values. For this study national breeding values for 909 Argentinean bulls were available; these records were used in a normal Interbull international evaluation and used as reference. The alternative method considers Argentinean bulls as unrecorded, but correlated to bulls in other countries. This method was used with seven different correlation matrices, giving seven alternatives to compare with the reference. Results showed correlation between reference and the alternative methods ranging between 0.926 and 0.973, and loss in genetic gain between 2.82% and 11.9%. This means that this alternative method could be used for countries that do not have national breeding values to submit for international evaluations

Marker-based adjustment of the additive relationship matrix for estimation of genetic parameters—an example using Eucalyptus cladocalyx

The effects of adjusting additive (numerator) relationship matrices (A) for inbreeding estimates taken from molecular markers were investigated using a small, model population of Eucalyptus cladocalyx. A number of individual-tree, mixed-models were compared, incorporating estimates of population- and family-level selfing and ancestral inbreeding applied either as average values to the entire population or as variable estimates for subpopulation and family groups. The consequences of ignoring inbreeding were inflated additive genetic variance estimates and underestimation of residual variance, with resulting inflation of heritability. We found models that correct for differential inbreeding at the subpopulation level give similar results to more complex ones including family-level estimates. Our analysis indicates that the commonly applied coefficient of relationship for first-generation eucalypt progeny of ρ = 1/2.5 appears to be quite suitable for correcting variance component and heritability estimates. However, if inbreeding is not specifically corrected for by adjustment of A, some minor rank changes of individual breeding values can occur, especially where levels of inbreeding vary among families, and some suboptimal selections and loss of genetic gain may ensue.

Mating animals by minimising the covariance between ancestral contributions generates less inbreeding without compromising genetic gain in breeding schemes with truncation selection

We reasoned that mating animals by minimising the covariance between ancestral contributions (MCAC mating) will generate less inbreeding and at least as much genetic gain as minimum-coancestry mating in breeding schemes where the animals are truncation-selected. We tested this hypothesis by stochastic simulation and compared the mating criteria in hierarchical and factorial breeding schemes, where the animals were selected based on breeding values predicted by animal-model BLUP. Random mating was included as a reference-mating criterion. We found that MCAC mating generated 4% to 8% less inbreeding than minimum-coancestry mating in the hierarchical and factorial breeding schemes without any loss in genetic gain. Moreover, it generated upto 28% less inbreeding and about 3% more genetic gain than random mating. The benefits of MCAC mating over minimum-coancestry mating are worthwhile because they can be achieved without extra costs or practical constraints. MCAC mating merely uses pedigree information to pair the animals more appropriately and is clearly a worthy alternative to minimum-coancestry mating and probably any other mating criterion. We believe, therefore, that MCAC mating should be used in breeding schemes where pedigree information is available.

Economic values of pork production related traits in Finland

The objective of the present study was to estimate economic values for sow efficiency and meat production traits in the Finnish pork production system including the consideration for subsidies. Economic values were estimated by developing a bio-economic model that describes the Finnish production system. Genetic improvement estimates for meat production traits were also developed in order to evaluate how much genetic gain is reduced due to selection for meat quality. Results showed that the highest economic values, when expressed in genetic standard deviations, were obtained for total number of piglets born (€2.07 per piglet), feed conversion ratio (€2.07 per feed unit per kg), and lean meat percentage (€1.69 per %). Economic values for litter size, piglet mortality, sows length of productive life, and lean meat percentage increased when subsidies were not accounted for in the bio-economic model. Results show further that meat quality should have 15–20 percent weight in the Finnish production trait index in order to prevent its deterioration. When the selection weights are 15–20% for meat quality, the expected loss in genetic gain is approximately 3 percent for other production traits when compared to selection indices where meat quality traits are not included.;